Initialize backend service with FastAPI and distilgpt2

- Created backend/requirements.txt
- Created backend/app.py with FastAPI and text generation pipeline
- Created backend/Dockerfile
- Created .github/workflows/sync_to_hub.yml for HF Space deployment

Dockerfile

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+FROM python:3.9
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY app.py .
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from transformers import pipeline
+
+app = FastAPI()
+
+# Initialize the text-generation pipeline
+# We can load this on startup to avoid loading it on every request,
+# although pipeline does caching, doing it globally is standard for this simple app.
+generator = pipeline("text-generation", model="distilgpt2")
+
+class ChatRequest(BaseModel):
+    text: str
+
+@app.get("/")
+def read_root():
+    return {"status": "Cool Shot Systems Backend Online"}
+
+@app.post("/chat")
+def chat(request: ChatRequest):
+    try:
+        # Generate response
+        response = generator(request.text, max_length=100, num_return_sequences=1)
+        return response[0]
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))

requirements.txt

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+fastapi
+uvicorn
+transformers
+torch